通过混合MRAC控制器减轻无人机的飞行性能误差

Aeshna Tanveer, Nimra Afzaal, S. Murawwat, Sabaina Aleem, Fatima Sayeda
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引用次数: 0

摘要

本研究探讨了四轴飞行器的建模、设计和控制,重点是减轻飞行性能误差,以补偿无人机的性能。它还探讨了一个数学模型的仿真和旋翼无人机系统的控制。此外,还介绍了一种微型无人机的CAD软件设计方法。然后使用自适应控制技术来设计无人机的四个子控制器,命名为高度控制,滚转,俯仰和偏航。它基本上是对经典模型参考自适应控制(Model Reference Adaptive Control, MRAC)方案的改造,即Hybrid MRAC,保证了比经典MRAC更好的上升时间性能。然后对存在干扰的控制器进行分析,证明自适应控制器比非自适应控制器对外部干扰具有更强的鲁棒性。最后,对于状态估计,应用扩展卡尔曼滤波器(EKF)来考虑现实世界中进一步降低无人机性能的传感器噪声
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mitigating Flight Performance Errors in UAVs through Hybrid MRAC controller
This research explores modelling, design, and control of quadcopters, focusing on mitigating flight performance errors that compensate the performance of Unmanned Aerial Vehicles (UAVs) performance. It also explores a mathematical model for simulation and a control of rotary-wing UAV systems. Moreover, it describes a design methodology for a micro-sized UAV in CAD software. Adaptive control techniques are then used to design four sub-controllers of UAVs named Altitude Control, Roll, Pitch, and Yaw. It is basically a remodeling of classical Model Reference Adaptive Control (MRAC) scheme, which is named Hybrid MRAC, ensuring a better rise time performance than classical MRAC. The controllers are then analyzed in the presence of disturbances to prove that adaptive controllers are more robust to external disturbances than non-adaptive ones. Lastly for state estimation, an Extended Kalman Filter (EKF) is applied to account for real-world sensor noises that further degrade the performance of UAV
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